The present invention generally relates to vehicle fuel efficiency improvement and related vehicle information management methods and systems. The present invention also relates to real-time monitoring and data analysis of vehicle dynamics and fuel efficiency data from a remote location. More specifically, various embodiments of the present invention relate to a fuel waste variable and parameter identification and analysis system and a related method of operation.
A significant fuel cost increase in transport vehicles and a newfound socioeconomic interest in energy efficiency in the last several decades have placed fuel efficiency a top priority in passenger vehicles and commercial vehicle management industry. Even though newer engine designs and vehicle design improvements provide incrementally-higher fuel efficiencies in passenger vehicles, commercial trucks, and other fleet vehicles, many vehicle operational factors, such as drivers' driving habits, traffic conditions, and vehicle maintenance and aftermarket fuel efficiency optimizations, cause over thirty percent variability in fuel efficiency of commercial vehicle operations.
In context of business profitability for commercial vehicle operations, a commercial vehicle fleet operator of ten trucks, with each truck averaging 15 miles per gallon, can achieve over 19.5 miles per gallon (i.e. a thirty percent improvement), if some of the vehicle operational factors are optimized. Because a truck in a commercial vehicle fleet routinely incurs several thousand dollars per month in fuel costs, a thirty percent improvement in fuel efficiency results in hundreds of dollars in fuel savings per month, for one truck alone. For the commercial vehicle fleet operator of ten trucks, following the above example, the fuel cost savings can accumulate to thousands of dollars per month.
Despite significant cost saving potential from improved fuel efficiency by optimizing aftermarket vehicle parts and drivers' driving behaviors, conventional methods of fuel efficiency improvement methods in passenger cars, commercial trucking, and fleet vehicles have been unsystematic and disjointed at best. For example, in conventional attempts to improve fuel efficiency, a truck driver may be encouraged to accelerate or decelerate more gently by a commercial trucking company. The commercial trucking company may also issue guidelines to its employees to drive under a recommended speed limit for optimal fuel efficiency. Furthermore, another conventional method of attempting fuel savings is simply displaying an auto manufacturer-implemented fuel efficiency number on a vehicle's dashboard, which is typically expressed as miles per gallon (MPG) or kilometers per liter (km/l). Unfortunately, these conventional fuel efficiency improvement efforts tend to be overly incoherent and sporadic, thereby failing to be effective strategies in most vehicle fleet operations. Furthermore, in case of a company ownership of trucks and commercial vehicles, a driver of a commercial vehicle may not have sufficient incentive or motivation to attempt fuel saving optimizations during his or her vehicular journey in the first place, because the driver is not personally responsible for fuel costs.
Therefore, it may be desirable to devise a novel electronic system that enables a commercial vehicle operator to track, manage, and improve fuel efficiency of its fleet vehicles in operation with a centralized electronic infrastructure. Furthermore, it may also be desirable to devise a novel electronic system that identifies, calculates, and analyzes a driver's driving behavior to pinpoint problematic fuel waste variables that are particular to a driver and to a particular vehicle, in an effort to improve the fuel efficiency of the particular vehicle by optimizing driving events, habits, and behaviors.
Moreover, it may also be desirable to devise a driving pattern analysis display interface generated from a novel electronic system to motivate both vehicle operating entities and vehicle drivers to understand, predict, and improve vehicle fuel efficiencies through mechanical improvement factors as well as non-mechanical improvement factors.